
Crack500 [1]}: containing 500 images of pavement cracks with granular backgrounds in a unified size of \(2560 \times 1440\)  with a few samples under uneven illumination. Due to the limitation in GPU memory and computation power, all the images are resized to \(256 \times 256\) .

CrackForest[2]}: containing 118 images of road cracks with labeled masks in a size of \(600 \times 800\)  with a part of samples with the interference of shadow and painted marks. We rotate the images with a range from 0 to 90 degrees, flip them vertically and horizontally, and randomly crop the flipped images with a size of \(256 \times 256\) . Ten thousands augmented images are split into the training and the validation set with a ratio of 9:1. The rest 1180 images are preserved for testing.

DCD [3]}: containing 521 images of infrastructure cracks with texture and misleading marks under various light condition.

GAPs [4]}: containing 509 images of pavement cracks with densely granular backgrounds under poor light conditions. DCD and GAPs are both integrated into an unified size of \(448 \times 448\) , following [5]}.

